Substitute Recommendation Task

Context:
- It can be solved by a Substitute Recommendation System (that implements an substitute recommendation algorithm).
See: Complementary Recommendations.

References

(Yu, Litchfield et al., 2019) ⇒ Hang Yu, Lester Litchfield, Thomas Kernreiter, Seamus Jolly, and Kathryn Hempstalk. (2019). “Complementary Recommendations: A Brief Survey.” In: The Proceedings of the 2019 International Conference on High Performance Big Data and Intelligent Systems (HPBD&IS). DOI:10.1109/HPBDIS.2019.8735479.
- QUOTE: ... For recommender systems, the ultimate target is to [[stimulate the purchasing activities of potential customers by retrieving the items that catch their personalized interests among the overloaded information. With this goal, such systems can be classified as substitute and complementary recommenders: substitute recommenders offer similar items to the source, complementary recommenders suggest items that are dissimilar to the source but are often sold with it as a companion item or service (such as a mobile phone (source) and case (complementary) ). ...

(McAuley et al., 2015a) ⇒ Julian McAuley, Rahul Pandey, and Jure Leskovec. (2015). “Inferring Networks of Substitutable and Complementary Products.” In: Proceedings of the 21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2015). ISBN:978-1-4503-3664-2 doi:10.1145/2783258.2783381
- QUOTE: ... To design a useful recommender system, it is important to understand how products relate to each other. For example, while a user is browsing mobile phones, it might make sense to recommend other phones, but once they buy a phone, we might instead want to recommend batteries, cases, or chargers. In economics, these two types of recommendations are referred to as substitutes and complements: substitutes are products that can be purchased instead of each other, while complements are products that can be purchased in addition to each other. Such relationships are essential as they help us to identify items that are relevant to a user's search. ...